3 citations · 6 across the 7 of their papers we have counts for
7 papers
Uncovering cognitive taskonomy through transfer learning in masked autoencoder-based fMRI reconstruction
Youzhi Qu, Junfeng Xia, Xinyao Jian +5
Data reconstruction is a widely used pre-training task to learn the generalized features for many downstream tasks. Although reconstruction tasks have been applied to neural signal…
Integration of cognitive tasks into artificial general intelligence test for large models
Youzhi Qu, Chen Wei, Penghui Du +10
During the evolution of large models, performance evaluation is necessarily performed to assess their capabilities and ensure safety before practical application. However, current…
A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network
Wenwei Luo, Wanguang Yin, Quanying Liu +1
The key to electroencephalography (EEG)-based brain-computer interface (BCI) lies in neural decoding, and its accuracy can be improved by using hybrid BCI paradigms, that is, fusin…
Explainable fMRI-based Brain Decoding via Spatial Temporal-pyramid Graph Convolutional Network
Ziyuan Ye, Youzhi Qu, Zhichao Liang +2
Brain decoding, aiming to identify the brain states using neural activity, is important for cognitive neuroscience and neural engineering. However, existing machine learning method…
Transfer learning to decode brain states reflecting the relationship between cognitive tasks
Youzhi Qu, Xinyao Jian, Wenxin Che +3
Transfer learning improves the performance of the target task by leveraging the data of a specific source task: the closer the relationship between the source and the target tasks,…
Kuramoto model based analysis reveals oxytocin effects on brain network dynamics
Shuhan Zheng, Zhichao Liang, Youzhi Qu +3
The oxytocin effects on large-scale brain networks such as Default Mode Network (DMN) and Frontoparietal Network (FPN) have been largely studied using fMRI data. However, these stu…
HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction
Wanguang Yin, Youzhi Qu, Zhengming Ma +1
Tensor decomposition is an effective tool for learning multi-way structures and heterogeneous features from high-dimensional data, such as the multi-view images and multichannel el…